DESCRIPTION (Applicant's abstract): The long-term goal of this study is to develop and use bioinformatics tools for gene expression array data analysis to discover and identify gene functions on a large scale. Currently, there is urgent need of methods that would help to validate and interpret expression array data. In this proposed study we intend to develop methods that integrate gene sequence similarity information with gene expression array data analysis. Our key hypothesis is that co-regulatory relationships between genes are to some extent conserved through evolution, and this conservation may be reflected in the expression profiles of homologous genes in various organisms. Once such conservation is established, it can help validate the gene clusters of expression profiles revealed by clustering algorithms and may assign new functional roles to uncharacterized genes by homology.